A Comprehensive Survey on GNSS Interferences and the Application of Neural Networks for Anti-jamming

Lorraine, Kambham Jacob Silva; Madhu, R.

doi:10.1080/03772063.2021.1953407

Cited by 8 publications

(7 citation statements)

References 49 publications

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“…Blanket jamming involves emitting signals with certain bandwidths and higher power on the frequency band where the satellite operates, causing receivers to lose their lock [18,19]. Studies in the literature [20][21][22][23][24] have investigated various blanket jamming methods, such as wideband noise jamming, partial-band noise jamming, single-tone jamming, multitone jamming, and pulse jamming. Their results demonstrated that blanket jamming has a wide coverage area and can effectively jam target receivers within a certain range.…”

Section: Related Workmentioning

confidence: 99%

LEO Satellite Downlink Distributed Jamming Optimization Method Using a Non-Dominated Sorting Genetic Algorithm

Tang,

Ding,

Zhang

2024

Remote Sensing

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Due to their low orbit, low-Earth-orbit (LEO) satellites possess advantages such as minimal transmission delay, low link loss, flexible deployment, diverse application scenarios, and low manufacturing costs. Moreover, by increasing the number of satellites, the system capacity can be enhanced, making them the core of future communication systems. However, there have been instances where malicious actors used LEO satellite communication equipment to illegally broadcast events in large sports stadiums or engage in unauthorized leakage of military secrets in sensitive military areas. This has become an urgent issue in the field of communication security. To combat and prevent abnormal and illegal communication activities using LEO satellites, this study proposes a LEO satellite downlink distributed jamming optimization method using a non-dominated sorting genetic algorithm. Firstly, a distributed jamming system model for the LEO satellite downlink is established. Then, using a non-dominated sorting genetic algorithm, the jamming parameters are optimized in the power, time, and frequency domains. Field jamming experiments were conducted in the southwest outskirts of Xi’an, China, targeting the LEO constellation of the China Satellite Network. The results indicate that under the condition that the jamming coverage rate is no less than 90%, the proposed method maximizes jamming power, minimizes time delay, and minimizes frequency compensation compared to existing jamming optimization methods, effectively improving the real-time jamming performance and success rate.

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Section: Related Workmentioning

confidence: 99%

LEO Satellite Downlink Distributed Jamming Optimization Method Using a Non-Dominated Sorting Genetic Algorithm

Tang,

Ding,

Zhang

2024

Remote Sensing

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“…The first one is interference, which affects not only the air transport itself, but intelligent transport systems as well [21]. The other problem is identification and location of mentioned GNSS signal interference [22]. This interference is typically not a concern for military and specialized applications, as they are often encrypted and have higher resistance to interference, utilizing two or more carrier frequencies for transmission [23].…”

Section: Introductionmentioning

confidence: 99%

Global Navigation Satellite Systems Signal Vulnerabilities in Unmanned Aerial Vehicle Operations: Impact of Affordable Software-Defined Radio

Novák,

Kováčiková,

Kandera

et al. 2024

Drones

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Spoofing, alongside jamming of the Global Navigation Satellite System signal, remains a significant hazard during general aviation or Unmanned Aerial Vehicle operations. As aircraft utilize various support systems for navigation, such as INS, an insufficient Global Navigation Satellite System signal renders Unmanned Aerial Vehicles nearly uncontrollable, thereby posing increased danger to operations within airspace and to individuals on the ground. This paper primarily focuses on assessing the impact of the budget friendly Software-Defined Radio, HackRF One 1.0, on the safety of Unmanned Aerial Vehicles operations. Considering the widespread use of Software-Defined Radio devices today, with some being reasonably inexpensive, understanding their influence on Unmanned Aerial Vehicles safety is crucial. The generation of artificial interference capable of posing a potential threat in expanding Unmanned Aerial Vehicles airspace is deemed unacceptable.

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“…The term global navigation satellite system (GNSS) typically refers to various global satellite navigation systems and their enhanced systems, including GPS in the United States, Galileo in Europe, GLONASS in Russia, and Beidou in China [1]. Due to the weak GNSS received power of −130 dBm, the GNSS spectrum is heavily immersed in environmental noise and exhibits elevated susceptibility to electromagnetic interference [2,3].…”

Section: Introductionmentioning

confidence: 99%

Localization of GNSS Spoofing Interference Source Based on a Moving Array Antenna

Liu,

Yang,

Chen

et al. 2023

Remote Sensing

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GNSS spoofing interference utilizes falsified navigation signals to launch attacks on GNSS systems, posing a significant threat to applications that rely on GNSS signals for positioning, navigation, and time services. Therefore, achieving effective localization of the sources causing spoofing interference is crucial in ensuring the secure operation of GNSS. This article proposes a method for locating GNSS spoofing interference sources using a moving array antenna. Firstly, the proposed method utilizes the inherent characteristics of the double-differenced carrier phase from the deception signals received by the array antenna to effectively extract the spoofing signals. Subsequently, by moving the antenna array, the original carrier phase single-difference data of multiple observation points for deception signals are fused to provide a cost function for direct localization of spoofing interference, and a solution method for the cost function is designed. The proposed method addresses the challenge of extracting and localizing GNSS spoofing interference weak signals, effectively avoiding the data correlation of traditional two-step methods for DOA estimation parameters and ensuring the location accuracy of spoofing interference and the robustness of the method. The effectiveness of the proposed method has been validated through simulation experiments, and its adaptability to factors such as errors in carrier phase measurements has been examined. The method exhibits strong applicability and is well-suited for the hardware platform of the GNSS nulling antenna, thereby enabling it to possess simultaneous capabilities in both anti-interference and spoofing interference localization.

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A Comprehensive Survey on GNSS Interferences and the Application of Neural Networks for Anti-jamming

Cited by 8 publications

References 49 publications

LEO Satellite Downlink Distributed Jamming Optimization Method Using a Non-Dominated Sorting Genetic Algorithm

LEO Satellite Downlink Distributed Jamming Optimization Method Using a Non-Dominated Sorting Genetic Algorithm

Global Navigation Satellite Systems Signal Vulnerabilities in Unmanned Aerial Vehicle Operations: Impact of Affordable Software-Defined Radio

Localization of GNSS Spoofing Interference Source Based on a Moving Array Antenna

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